Handling Uncertainty in Artificial Intelligence
Author | : Jyotismita Chaki |
Publisher | : Springer Nature |
Total Pages | : 111 |
Release | : 2023-08-06 |
ISBN-10 | : 9789819953332 |
ISBN-13 | : 9819953332 |
Rating | : 4/5 (332 Downloads) |
Download or read book Handling Uncertainty in Artificial Intelligence written by Jyotismita Chaki and published by Springer Nature. This book was released on 2023-08-06 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates different methods (as well as real-life examples) of handling uncertainty like probability and Bayesian theory, Dempster-Shafer theory, certainty factor and evidential reasoning, fuzzy logic-based approach, utility theory and expected utility theory. At the end, highlights will be on the use of these methods which can help to make decisions under uncertain situations. This book assists scholars and students who might like to learn about this area as well as others who may have begun without a formal presentation. The book is comprehensive, but it prohibits unnecessary mathematics.